TY - JOUR
T1 - Proteome informatics for cancer research
T2 - From molecules to clinic
AU - Brusic, Vladimir
AU - Marina, Ovidiu
AU - Wu, Catherine J.
AU - Reinherz, Ellis L.
PY - 2007/3
Y1 - 2007/3
N2 - Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.
AB - Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.
KW - Bioinformatics
KW - Melanoma
KW - Software
UR - http://www.scopus.com/inward/record.url?scp=33947732714&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33947732714&partnerID=8YFLogxK
U2 - 10.1002/pmic.200600965
DO - 10.1002/pmic.200600965
M3 - Review article
C2 - 17370257
AN - SCOPUS:33947732714
VL - 7
SP - 976
EP - 991
JO - Proteomics
JF - Proteomics
SN - 1615-9853
IS - 6
ER -